Geologic models are commonly used in the petroleum exploration and production industry to characterize petroleum reservoirs and depositional basins. For example, such models, which are computer-based representations of a volume of the subsurface, are frequently used in simulating the performance of a reservoir over time. The term “geologic model” may represent either the entire volume of a subsurface volume of interest to an analyst, or a single region of interest within that larger subsurface volume. Geologic models are generally in the form of a three-dimensional array of blocks, sometimes referred to as cells, or, less commonly, an array of points. Hereafter, without limitation, geologic models will be referred to as being constructed of an array of blocks.
A geologic model's characterization of the subsurface derives from the assigning of geologic rock properties, such as lithology, porosity, acoustic impedance, permeability, and water saturation, to each of the blocks in the model. The process of assigning values to the blocks is generally constrained by stratigraphic or structural surfaces and boundaries, such as facies changes, that separate regions of different geologic and geophysical properties within the subsurface. The importance of the values that are assigned to each of the blocks results from the fact that the spatial continuity of the rock properties in a petroleum reservoir can significantly influence the characteristics of fluid flow from the reservoir. More accurate geologic model characterizations of rock property spatial continuity allow more accurate planning of the production that can be attained from the reservoir. For this reason, methods of improving the accuracy of the characterization of rock property spatial continuity in geologic models are desired.
Industry presently characterizes the three-dimensional spatial continuity of a rock property in a geologic model using geostatistical algorithms. These algorithms use a variogram to quantify the spatial variability of the rock property as a function of both separation distance and direction between individual blocks in the model. The algorithms also assume stationarity in the geologic characteristics of the modeled subsurface region. In other words, geostatistical algorithms assume that a modeled rock property can be represented by a single set of statistical measures, which are often referred to as global measures. For example, a single global variogram model would be used to represent the spatial continuity of the modeled rock property over all blocks of the entire model. A limitation of this method, however, is that it is well known that the geologic characteristics of the subsurface are non-stationary. Specifically, the spatial continuity of a rock property may change locally within the model, sometimes according to predictable or measurable trends. These local changes will be referred to as local measures, and may be characterized by local variogram models.
At present, there are no geostatistical methods available to the industry that allow modeling of continuous spatial trends in rock-property continuity within a modeled region of the subsurface. Examples of properties in which the ability to model such trends would be beneficial include porosity, permeability, and shale volume. The benefit of such an ability would be that if the continuity of spatial trends within the region of the subsurface could be determined, then any such trends could be built into the geologic model. Furthermore, by controlling continuity trends in these properties a model can be developed which more effectively represents subsurface trends in such characteristics as bed thickness, also referred to as vertical continuity, and body dimension, also referred to as lateral continuity. The reservoir performance that is simulated based on the model would then be more likely to be an accurate prediction of the future performance of the reservoir. The present invention provides the geologic modeler with this ability.